Paper Citation Record · LEDGER

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios

As of 6 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2507.18177.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2507.18177 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-19T02:58:33.899093Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T20:46:37.512447Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-05-20T20:49:00.796510Z

Reference resolution

37 of 37 outbound references displayed

verified exact6
verified fuzzy14
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e28955a6-2866-4bca-bb54-76ddd4aed7bc · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.557373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 329825eb-cd27-4c0d-95f9-1725c0279474 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.582576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 409f3ff7-e77e-4107-916c-a8b5a4268731 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.571046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 304e8c90-ee93-43be-bfa3-1c8d002290f7 · outbound

This paper cites Vaswani, N.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Vaswani, N

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.567594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e3eba464-6296-4107-8bf1-b138244772d2 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-19T03:02:00.331679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7f2dd941-05a5-4ae9-b69f-e5d799f9af3d · outbound

This paper cites Shamshad, S.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Shamshad, S

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.586371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8fefb50d-e4a2-4ac7-8efb-3992ee22337f · outbound

This paper cites Recurrent Neural Networks (RNNs): A gentle Introduction and Overview.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Recurrent Neural Networks (RNNs): A gentle Introduction and Overview

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:02:00.319467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 46d659e8-e482-49d9-ad21-f87fec51383b · outbound

This paper cites Understanding LSTM -- a tutorial into Long Short-Term Memory Recurrent Neural Networks.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Understanding LSTM -- a tutorial into Long Short-Term Memory Recurrent Neural Networks

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:02:00.326088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 65f28831-9643-4f11-9b45-41630c8ded15 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.593981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6e0f75bd-065e-49b8-9cfa-3bfa45295816 · outbound

This paper cites Hatamizadeh, Y.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Hatamizadeh, Y

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.564126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 463a27ca-0888-4746-b7d4-7f2a0afe6025 · outbound

This paper cites Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:02:00.312933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3c9f6d01-0be3-4c86-924e-7dbef70d4ffd · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.578740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bef64fff-d593-426c-b617-6eeefff65ced · outbound

This paper cites U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-19T03:02:00.337200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0fd043d9-e62c-457b-893e-1a33edf996e3 · outbound

This paper cites Litjens, T.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Litjens, T

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.590109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 42778ba1-6b14-4b1d-8cc1-ab37dd9c58c7 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.574921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 02b809bc-94cd-4070-a207-f4d36941f10e · outbound

This paper cites Hussain, Y.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Hussain, Y

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.560660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 87fd35fd-8b89-4bb3-9614-9a52b84ae4ea · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.624380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 788502d9-8fc4-45e6-abd5-b2179c4509c7 · outbound

This paper cites Power, Y.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Power, Y

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.605750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3fd94e51-2119-417e-980b-055885b48f03 · outbound

This paper cites Shao, X.-J.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Shao, X.-J

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.612829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5dab42ad-3ac8-486a-9fc0-ec8f858286d1 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.601778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 49c99444-6388-46d1-801f-481e8699c080 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.597750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 618bc4ed-d452-4585-88cf-a0d34256a2af · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.609308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 083d635d-6763-4ebb-998a-488c7611da38 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.616396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 77bb016a-7695-4bf2-a57f-2ac60cba0086 · outbound

This paper cites Bakas, M.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Bakas, M

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.620176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cd5e9c95-301c-49d3-8942-513be65b07bf · outbound

This paper cites Bakas, H.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Bakas, H

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.628328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cfa25a61-89d7-4482-a605-38e994dcb983 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.632152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f48fe444-fc09-4cb5-9d8c-016265f59834 · outbound

This paper cites Alzubaidi, J.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Alzubaidi, J

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.635895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3541f402-0e31-4592-94ec-56e656c7fcbd · outbound

This paper cites Ulyanov, A.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Ulyanov, A

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.639493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7717540c-8bca-4f23-bb7a-6ee3e615be74 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.668891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation dab6f044-edcd-44df-8b06-532b6ce4790c · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Gaussian Error Linear Units (GELUs)

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-05-19T03:02:00.300577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f0b486db-db52-47e3-91d4-11603a10b14c · outbound

This paper cites Nalatore, M.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Nalatore, M

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.661819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ae37bec9-dd11-48a3-bfb3-f9b5aba7be03 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.665280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b995e4d1-e377-437e-82d5-d1236e4e034b · outbound

This paper cites Isensee, P.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Isensee, P

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.658238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ed76e894-c681-4501-9e46-963bf86b152f · outbound

This paper cites Myronenko, 3d mri brain tumor segmentation using autoencoder regular- ization, in: A.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Myronenko, 3d mri brain tumor segmentation using autoencoder regular- ization, in: A

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.654458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 37c6cbfc-570d-40a3-8863-28b97ebfefab · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.650591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 07d7b4ba-3204-4fcc-b75f-deee8284c6c4 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.647014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f0d5d63f-764e-460b-a3f6-8ff9ac5c5651 · outbound

This paper cites an unresolved cited work.

Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.643389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

Observation 56b68727-be40-4231-82c0-e11367ed0f9f · inbound

StampFormer: A Physics-Guided Material-Geometry-Coupled Multimodal Model for Rapid Prediction of Physical Fields in Sheet Metal Stamping cites this paper.

StampFormer: A Physics-Guided Material-Geometry-Coupled Multimodal Model for Rapid Prediction of Physical Fields in Sheet Metal Stamping Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-05-20T20:49:00.799502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.